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The Precise Relationship Between Model for End‐Stage Liver Disease and Survival Without a Liver Transplant
Author(s) -
VanDerwerken Douglas N.,
Wood Nicholas L.,
Segev Dorry L.,
Gentry Sommer E.
Publication year - 2021
Publication title -
hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.488
H-Index - 361
eISSN - 1527-3350
pISSN - 0270-9139
DOI - 10.1002/hep.31781
Subject(s) - liver disease , medicine , model for end stage liver disease , liver transplantation , confidence interval , survival analysis , overall survival , stage (stratigraphy) , transplantation , biology , paleontology
Background and Aims Scores from the Model for End‐Stage Liver Disease (MELD), which are used to prioritize candidates for deceased donor livers, are widely acknowledged to be negatively correlated with the 90‐day survival rate without a liver transplant. However, inconsistent and outdated estimates of survival probabilities by MELD preclude useful applications of the MELD score. Approach and Results Using data from all prevalent liver waitlist candidates from 2016 to 2019, we estimated 3‐day, 7‐day, 14‐day, 30‐day, and 90‐day without‐transplant survival probabilities (with confidence intervals) for each MELD score and status 1A. We used an adjusted Kaplan‐Meier model to avoid unrealistic assumptions and multiple observations per person instead of just the observation at listing. We found that 90‐day without‐transplant survival has improved over the last decade, with survival rates increasing >10% (in absolute terms) for some MELD scores. We demonstrated that MELD correctly prioritizes candidates in terms of without‐transplant survival probability but that status 1A candidates’ short‐term without‐transplant survival is higher than that of MELD 40 candidates and lower than that of MELD 39 candidates. Our primary result is the updated survival functions themselves. Conclusions We calculated without‐transplant survival probabilities for each MELD score (and status 1A). The survival function is an invaluable tool for many applications in liver transplantation: awarding of exception points, calculating the relative demand for deceased donor livers in different geographic areas, calibrating the pediatric end‐stage liver disease score, and deciding whether to accept an offered liver.

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